Abstract
Background and purpose
Methamphetamine (MA) use disorder is associated with widespread disruption of large-scale brain networks involved in cognitive control, attention, and salience processing. Resting-state fMRI (rs-fMRI) provides a means to characterize these alterations; however, little is known about the capacity for functional network reorganization following targeted intervention. The purpose of this study was to evaluate changes in large-scale and local functional connectivity following psilocybin administration in individuals with MA use disorder.Materials and methods
In this exploratory prospective longitudinal study, participants with MA use disorder underwent rs-fMRI before and after psilocybin administration alongside psychotherapy. Large-scale functional connectivity was assessed across canonical resting-state networks, including the default mode, salience, dorsal attention, and executive control networks. Local connectivity was evaluated using regional homogeneity (ReHo). Connectivity changes were examined in relation to clinical measures of MA use, craving, and psychological distress.Results
Following intervention, reorganization of functional connectivity was observed within and between attentional, default mode, and salience networks. Improvements in network integration were accompanied by complementary shifts in local neural synchrony, with postintervention increases in ReHo observed within frontal and sensorimotor regions. Greater MA reductions in use were associated with recovery of frontostriatal and attentional connectivity, whereas reductions in psychological distress correlated with strengthened integration of attentional and prefrontal-striatal circuits.Conclusions
Psilocybin administration was associated with measurable reorganization of both large-scale network connectivity and local functional coherence in individuals with MA use disorder. These findings provide preliminary evidence for the distributed nature of brain network dysfunction in stimulant addiction and support the potential utility of multimodal rs-fMRI metrics as imaging biomarkers of network-level plasticity.